Multiple regression prediction model for cutting forces and surface roughness in micro-milling of TA2

Titanium and its alloys are widely used in the biomedical fields, such as implant, surgical instrument, and the dynamic compression plate. Compared with Ti-6Al-4V, TA2 has lower thermal conductivity, better affinity, and adhesion, resulting in poor machinability during processing. Optimum machining solution is required to improve the surface quality, to reduce the wear of tool, and to save the cost of production. This manuscript presents experimental results of micro-milling test conducted on TA2 with changing cutting parameter, two coating tool, and different cooling methods. Also, the orthogonal regression prediction mathematical model of pure titanium micro-milling of TA2 cutting force and surface temperature have been obtained. And the model provides a reference value for the medical pure titanium processing, aiming at the smallest cutting force and surface roughness with optimum parameters.